Data quality involves the processes, policies, and techniques used to ensure that data meets predefined standards of accuracy, completeness, consistency, and reliability. It encompasses activities such as data profiling, cleansing, validation, and monitoring to identify and rectify errors, anomalies, and inconsistencies within data sets.
Metadata management focuses on the creation, documentation, and maintenance of metadata, which provides context and structure to data assets. Metadata includes information about the characteristics, attributes, and relationships of data elements, such as their source, format, meaning, and usage.